https://static.poder360.com.br/2020/10/Anuario-2020-FINAL.pdf
x<-1980:2018
y<-c(11.69,12.56,12.57,13.77,15.32,15.00,15.26,16.89,16.78,20.30,22.22,20.94,19.21,20.20,21.23,23.84,24.78,25.39,25.94,26.20,27.35,27.86,28.53,29.14,26.94,26.13,26.61,26.20,26.72,27.18,27.80,27.45,29.41,28.55,29.82,28.89,30.33,31.59,27.8)
z<-c(rep(NA,24),y[25:39])
y<-c(y[1:25],rep(NA,14))
resultado2<-data.frame(x=x,y=y,z=z)
fig <- plot_ly(resultado2, x = x, y = y, type = 'scatter', mode = 'lines',line = list(color = 'rgb(255, 255, 255)',dash = 'dash', width = 2),name = 'Taxa de Homicídios (1980-2003)')
fig <- fig %>% add_trace(y = ~z,line = list(color = 'rgb(205, 12, 24)', width = 3,dash = F),name = 'Taxa de Homicídios (2004-2018)')
fig <- fig %>% layout(legend = list(x = 0.1, y = 0.9),plot_bgcolor='rgb(25,25,25)', paper_bgcolor='rgb(0, 0, 0)',
yaxis = list(title="Homicídios por 100 mil habs.",zeroline = T, tickfont = list(size = 26,color = 'rgba(255, 255, 255, .9)'), titlefont = list(size = 26,color = 'rgba(255, 255, 255, .9)')),
xaxis = list(title="",zeroline = T,tickfont = list(size = 26,color = 'rgba(255, 255, 255, .9)'),titlefont = list(size = 26,color = 'rgba(255, 255, 255, .9)')))
figMannKendall(y)## tau = 0.9, 2-sided pvalue =< 2.22e-16##
## Call:
## lm(formula = taxa ~ armas, data = resultado2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11.812 -4.939 -1.096 6.529 10.129
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.886e+01 1.673e+00 17.249 2.15e-15 ***
## armas -1.050e-04 2.638e-05 -3.978 0.000524 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6.84 on 25 degrees of freedom
## Multiple R-squared: 0.3877, Adjusted R-squared: 0.3632
## F-statistic: 15.83 on 1 and 25 DF, p-value: 0.0005237df<-read.csv("taxa_homicidios_crimes_violentos.txt", sep="\t",h=T)
armas<-df$armas
total_crimes<-df$TAXA_CRIMES_VIOLENTOS
taxa_crimes_violentos<-df$homicidios
x<-armas
y<-total_crimes
z<-taxa_crimes_violentos
resultado2<-data.frame(armas=x,taxa=y,total=z)
fit <- lm(taxa~total,data=resultado2)
fig3<-resultado2 %>%
plot_ly(x = ~armas) %>% add_lines(x = ~armas, y = fitted(fit),line=list(color='red')) %>%
add_markers(y = ~total,color = 'rgba(152, 0, 0, .8)',marker=list(size=15,color = 'rgba(255, 255, 255, .9)',line = list(color = 'rgb(205, 12, 24)',width = 3))) %>%
layout(showlegend = FALSE,
#title = 'ARMAS x HOMICÍDIOS',font=list(size = 16,color = 'rgba(255, 255, 255, .9)'),
plot_bgcolor='rgb(25,25,25)', paper_bgcolor='rgb(0, 0, 0)',
yaxis = list(title="Total de crimes violentos",zeroline = T, tickfont = list(size = 26,color = 'rgba(255, 255, 255, .9)'), titlefont = list(size = 26,color = 'rgba(255, 255, 255, .9)')),
xaxis = list(title="Armas registradas (SINARM)",zeroline = T,tickfont = list(size = 26,color = 'rgba(255, 255, 255, .9)'),titlefont = list(size = 26,color = 'rgba(255, 255, 255, .9)')))
fig3## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels
## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levelssummary(fit)##
## Call:
## lm(formula = taxa ~ total, data = resultado2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -17.9780 -7.3391 -0.2354 8.4424 12.1138
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.449e+01 2.643e+00 9.267 1.46e-09 ***
## total 1.669e-04 1.319e-03 0.126 0.9
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8.738 on 25 degrees of freedom
## Multiple R-squared: 0.0006397, Adjusted R-squared: -0.03933
## F-statistic: 0.016 on 1 and 25 DF, p-value: 0.9003######################################################################